Comparison between Modified Weighted Pareto Distribution and Many other Distributions

Main Article Content

Mahmood A. Shamran
https://orcid.org/0000-0001-8506-3876
Asmaa A. Mohammed
Iden H. Alkanani

Abstract

 


In 2020 one of the researchers in this paper, in his first research, tried to find out the Modified Weighted Pareto Distribution of Type I by using the Azzalini method for weighted distributions, which contain three parameters, two of them for scale while the third for shape.This research compared the distribution with two other distributions from the same family; the Standard Pareto Distribution of Type I and the Generalized Pareto Distribution by using the Maximum likelihood estimator which was derived by the researchers for Modified Weighted Pareto Distribution of Type I, then the Mont Carlo method was used–that is one of the simulation manners for generating random samples data in different sizes ( n= 10,30,50), and in different initial values for each Pareto distribution family being used in the research. A comparison was done by using Akaike Information Criteria, Corrected Akaike Information Criteria, and Bayesian Information Criteria

Article Details

How to Cite
1.
Comparison between Modified Weighted Pareto Distribution and Many other Distributions. Baghdad Sci.J [Internet]. 2023 Jun. 20 [cited 2024 Apr. 27];20(3(Suppl.):1108. Available from: https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/8169
Section
article

How to Cite

1.
Comparison between Modified Weighted Pareto Distribution and Many other Distributions. Baghdad Sci.J [Internet]. 2023 Jun. 20 [cited 2024 Apr. 27];20(3(Suppl.):1108. Available from: https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/8169

References

Azzalini A. A Class of Distributions Which Includes the Normal Ones. Scand J Stat. 1985 Jan 1; 12(2): 171-178. http://www.jstor.org/stable/4615982.

Para BA, Jan TR. On Three Parameter Weighted Pareto Type II Distribution: Properties and Applications in Medical Sciences. Amisl. 2018; 6(1): 13-26. http://dx.doi.org/10.18576/amisl/06010.

Alkanani IH, Salman SG. Bayes and Non-Bayes Estimation Methods for the Parameter of Maxwell-Boltzmann Distribution. Baghdad Sci J. 2017; 14(4). http://dx.doi.org/10.21123/bsj.2017.14.4.0808

Nagatsuka H, Balakrishnan N. Efficient Likelihood-Based Inference for the Generalized Pareto Distribution. Ann Inst Stat Math. 2021 Dec; 73(6): 1153-85.

Omekam IV, Popoola J, Gatta NF, Adejumo AO. Some Extended Pareto Type I Distributions. Ife J Sci. 2022 Oct 13; 24(2): 265-76. https://dx.doi.org/10.4314/ijs.v24i2.8.

Pho KH, Ly S, Ly S, Lukusa TM. Comparison Among Akaike Information Criterion, Bayesian Information Criterion and Vuong's Test in Model Selection: A Case Study of Violated Speed Regulation in Taiwan. J Adv Eng Comput. 2019 Mar 31;3(1): 293-303. http://dx.doi.org/10.25073/jaec.201931.220.

Portet S. A Primer on Model Selection Using the Akaike Information Criterion. Infect Dis Model. 2020 Jan 1; 5: 111-28. https://doi.org/10.1016/j.idm.2019.12.010.

Pham MH, Tsokos C, Choi BJ. Maximum likelihood estimation for the generalized pareto distribution and goodness-of-fit test with censored data. J Mod Appl Stat Methods. 2019;17(2):11.. https://dx.doi.org/10.22237/jmasm/1553261471.

Cavanaugh JE, Neath AA. The Akaike Information Criterion: Background, Derivation, Properties, Application, Interpretation, and Refinements. WIREs Comput Stat. 2019: e1460. https://doi.org/10.1002/wics.1460.

Sahmran MA. Modified Weighted Pareto Distribution Type I (MWPDTI). Baghdad Sci J. 2020 Sep 1; 17(3): 869-877. https://doi.org/10.21123/bsj.2020.17.3.0869.

Al Sarraf NM, Mohana FA, Kamal GI. About Estimating Pareto Distribution Parameters. J Rafidain Uni Coll Sci. 2020; 2020(46): 431-40.

Similar Articles

You may also start an advanced similarity search for this article.